The text mining handbook : advanced approaches in analyzing unstructured data /
Ronen Feldman, James Sanger.
- Cambridge ; New York : Cambridge University Press, 2007.
- xii, 410 p. : ill. ; 27 cm.
Includes bibliographical references (p. 335-387) and index.
Introduction to text mining -- Core text mining operations -- Text mining preprocessing techniques -- Categorization -- Clustering -- Information extraction -- Probabilistic models for information extraction -- Preprocessing applications using probabilistic and hybrid approaches -- Presentation-layer considerations for browsing and query refinement -- Visualization approaches -- Link analysis -- Text mining applications.
Text mining tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.